Co-authored by Peter Bentley and Daryl Bowden.
For many years we have worked in a business that has focused on relationships. Many institutional brokers / banks have focused on using highly paid humans to engage with their clients to deliver: data, content, hopefully some additional insight and execute.
To engage with clients and manage front line staff, the focus has been on leveraging data - internal and external. The evolution started with: masses of paper, spreadsheets and then management information and research. Delivering data (in the broadest meaning of the word) to clients and using data to monitor engagement; measuring cause and effect.
CRM existed to capture the interactions and dashboards became the way to understand them. External parties started to benchmark the data; “share of wallet” and “votes received” became additional subsets that were swallowed up and incorporated into (at times) pretty graphical displays that were printed out to sit on a manager’s desk.
There were, however, a couple of deep flaws embedded in this workflow: firstly, this process was focused on management; to reward good outcome and penalise poor. It was never used to empower the front office and client outreach. Secondly, there was little realisation that the data available and the speed it was being generated at, was beyond human cognition.
Content relevant for clients was collated through read-throughs, morning meetings, news, research and dialogue and yet it was always focused on finding the narrowest subject matter to target the broadest number of clients. Thus, nothing was tailored to a specific client.
Internally, the best firms started to use data to understand clients but the whole process took time. Data was kept in multiple silos that required humans to manipulate it into something edible. There was also duplication; each manager had their own COO to manage this process, leveraging the same data sets to build their own reports. As the data cottage industry bloomed, the questions that should be asked constantly throughout a trading day were missed:
Where is the repeatable success?
What should I talk about / focus on?
What did I do last time this happened?
Where did we generate revenues?
Who will be most interested?
For all the talk of disruption and fintech, the industry has not moved forward in how we use data to empower. CRM still captures information but what goes in rarely comes out enhanced; it is at best a statement of fact rather than a proactive tool to drive growth.
The inherent flaws within this process means that there is too much data, that is not leveraged properly, it takes too much time to manipulate and if it hits the right target it is by accident.
The future - where are we going?
Times are changing - fintech businesses are sitting on more and broader data than any CRM can contain, external data sets have extended beyond benchmarks and news, tweets, macro events have the same impact on cause and effect as who emailed who.
One of the benefits of being human is our ability to take a variety of different information sets, to ingest them and learn to consider the nuance and then make a decision. But our flaw is that (assuming complete access to all the known information) the ability to do this is limited by our capacity.
Therein lies opportunity cost. Beautiful workflow, analysis and assessment could be targeted at completely the wrong focal point using the wrong data.
According to PWC, businesses in finance are using less than 0.5% of their data. This in an age when the best performing funds in the industry are all powered by machines, alternate data and systematization. There is a huge disconnect.
But technology is there to help and some of the largest investment banks are spending heavily on technology. One specific area ‘chatbots’ is interesting in particular…
Helping people help themselves - Chatbots:
Chatbots are a standard part of a retail client journey. Whether you contact your bank online or look to query your phone bill, when you ask a question you are more than likely to be speaking with a chatbot.
The value proposition is simple: why phone an intermediary when all you want to do is change a policy or request a statement? It is estimated that 80% of call centre queries cover a regular 20 questions, ones that once identified, chatbots can easily assist with. This is also true in the more dynamic capital market businesses and most questions can be more effectively answered by a digital agent – particularly those focal questions we outlined earlier.
Key to any chatbot discussion is artificial intelligence (AI) and it is driving the growth of virtual assistants, such as Amazon’s Alexa. The same technology can be applied to capital markets where, for years, decisions have often been made without consistent availability of the known information. And worryingly, that the “known” information may not incorporate: what happened last time this occurred? What was the outcome? And what is the best course of action?
Therein lies the opportunity: augmenting a sales, research and trading process merely requires an understanding of the cognitive workflow and access to the right data sets. Real productivity gains can be achieved, leaving the highly paid human to focus on the valued elements of client engagement. The application of the bot might be to alert you to a new event or liquidity; suggest an asset to own based on your investment style; write a customised morning note and so much more.
More importantly for Brokers, it can connect external client consumption to internal engagement data; allowing a sales person or sales trader to focus specific information at the client most likely to consume it immediately.
This leads to a customer-oriented environment where proactive chatbots play a major role in enhancing the front office. With digital disruption hitting the banking market, the incumbents will have to use everything in their arsenal to stay relevant. This is just as likely to be true in wealth management, retail broking and capital markets.
It also means management can focus on refining the workflow, directing focus and talent management rather than analysing how many calls someone has made.
CRM data quality will perpetually improve as it is in the sales person’s interest to improve the data. Because if a chatbot can tell a sales person who and when to call and what to say, it can certainly update a CRM on the sales person's behalf.
Therefore, chatbots have the ability to augment human cognition. To speed up the decision-making process and to become a digital assistant on steroids. Opportunity cost is mitigated as bionic client-facing staff are pointed at the right opportunity, at the right time, with the right information to hand. Thus allowing management to focus on management, rather than analysis and data gazing.
The question that needs to be asked is, if JP Morgan ($10.8bn), Citibank ($8bn), Goldman ($8bn), Morgan Stanley ($4bn) are spending billions on this sort of technology and your budget does not quite extend that far, how do you compete? At which point you it might be worth contacting us.